• Journal of Institute of Control, Robotics and Systems
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• v.19 no.3
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• pp.177-182
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• 2013

This paper proposes an input-constrained reference tracking control of a converter model. To this end, first it is shown that the bilinear converter model can be equivalently represented by a linear uncertain model belonging to a polytopic set. Then, an input-constrained tracking control scheme for the linear uncertain model is designed based on recently proposed tracking control scheme. The control scheme yields not only a stabilizing control gain but also a feasible and invariant set for the converter model. Finally, simulation results show that the state trajectory always stays in the feasible and invariant set and that the output tracks the given reference while satisfying the input constraint.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.11 no.7
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• pp.261-266
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• 2001

The flexural vibration of laminated composite beams with active and passive constrained layer damping has been investigated to design a structure with maximum possible damping capacity. The equations of motion are derived fro flexural vibrations of symmetrical,. multi-layer laminated beams. The damping ratio and model damping of the first bending mode are calculated by means of iterative complex eigensolution method. The direct negative velocity feedback control is used for the active constrained layer damping. It is shown that the flexible laminated beam is more effective in the vibration control for both active and passive constrained layer damping. and this paper addresses a design strategy of laminated composite under flexural vibrations with constrained layer damping.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2121-2125
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• 2003

This paper proposes a fast distributed constrained power control (FDCPC) with non-stationary relaxation factor to next power update in CDMA cellular power control system. We review unconstrained control algorithms, the distributed power control (DPC), unconstrained second order power control (USOPC) and DPC with stationary relaxation factor (DPCSRF). Under the unconstrained condition, the convergence analysis shows theoretically that the convergence rate of DPC is the fastest one. However, under the constrained control algorithms, DCPC is not the fastest one any more because of transmission power constraint. To improve the convergence speed, the DCPC with non-stationary relaxation factor (FDCPC) are proposed. Under the constrained condition, the convergence rate of FDCPC outperforms that of DCPC and CSOPC.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.3
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• pp.159-163
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• 2001

An input constrained receding horizon predictive control algorithm for uncertain systems with nonzero set points is proposed. for constant nonzero set points, models with uncertainty can be converted into an augmented incremental system through the use of integrators and the problem is transformed into a zero-state regulation problem for the incremental system. But the original constraints on inputs are converted into constraints on the sum of control inputs at each time instants, which have not been dealt in earlier constrained robust receding horizon control problems. Recursive state bounding technique and worst case minimizing strategy developed in earlier works are applied to the augmented incremental system to yield an offset error free controller. The resulting algorithm is formulated so that it can be solved using LP.

• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.418-429
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• 2018

This paper studies the decentralized position/force control problem for constrained reconfigurable manipulator without torque sensing. A novel joint torque estimation scheme that exploits the existing structural elasticity of the manipulator joint with harmonic drive model is applied for each joint module. Based on the estimated joint torque and dynamic output feedback technique, a decentralized position/force control strategy is presented. In order to solve the problem of controller parameter perturbation, the non-fragile robust technique is introduced into the dynamic output feedback controller. Subsequently, the stability of the closed-loop system is proved using the Lyapunov theory and linear matrix inequality (LMI) technique. Finally, two 2-DOF constrained reconfigurable manipulators with different configurations are applied to verify the effectiveness of the proposed control scheme in numerical simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.536-536
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• 2000

In this paper, we show based on Lyapunov theorem that the closed loop system with the constrained H$_{\infty}$ optimal controller is exponentially stable. Then the on-line feedback implementation of the constrained H$_{\infty}$ optimal control based on quadratic programs is proposed.

• Journal of Information Technology Applications and Management
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• v.13 no.4
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• pp.291-302
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• 2006

The current paper proposes fast distributed constrained power control (FDCPC) with a non stationary relaxation factor as the next power update for CDMA cellular power control systems. A review is also given of unconstrained control algorithms: distributed power control (DPC), unconstrained second order power control (USOPC), and DPC with a stationary relaxation factor (DPCSRF) To improve the performance of outage probability convergence, DCPC with a non stationary relaxation factor (FDCPC) is proposed. Under constrained conditions, the convergence rate of FDCPC is shown to outperform that of DCPC and constrained second order power control(CSOPC).

• 전기의세계
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• v.49 no.9
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• pp.4-8
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• 2000

Recently we have shown based on Lyapunov theorem that the closed loop system with the constrained infinite horizon H$\infty$ optimal controller is exponentially stable. moreover the on-line feedback implementation of the constrained infinite horizon H$\infty$ optimal control based on quadratic programs has been proposed. n this paper we summarize and discuss these results.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.1
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• pp.19-30
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• 2013

Recently, the constrained index tracking problem, in which the task of trading a set of stocks is performed so as to closely follow an index value under some constraints, has often been considered as an important application domain for control theory. Because this problem can be conveniently viewed and formulated as an optimal decision-making problem in a highly uncertain and stochastic environment, approaches based on stochastic optimal control methods are particularly pertinent. Since stochastic optimal control problems cannot be solved exactly except in very simple cases, approximations are required in most practical problems to obtain good suboptimal policies. In this paper, we present a procedure for finding a suboptimal solution to the constrained index tracking problem based on approximate dynamic programming. Illustrative simulation results show that this procedure works well when applied to a set of real financial market data.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.1
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• pp.67-71
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• 2009

This paper presents a rank-constrained linear matrix inequality (LMI) approach to the design of a multi-objective controller such as $H_2/H_{\infty}$ control. Multi-objective control is formulated as an LMI optimization problem with a nonconvex rank condition, which is imposed on the controller gain matirx not Lyapunov matrices. With this rank-constrained formulation, we can expect to reduce conservatism because we can use separate Lyapunov matrices for different control objectives. An iterative penalty method is applied to solve this rank-constrained LMI optimization problem. Numerical experiments are performed to illustrate the proposed method.